class_docstr: 存在多个auto_collate和多个collate_fn时候，对一个批次数据集应用哪个auto_collate和collate_fn的问题
class_docstr_tok: ["\u5b58\u5728\u591a\u4e2aauto_collate\u548c\u591a\u4e2acollate_fn\u65f6\u5019\uff0c\u5bf9\u4e00\u4e2a\u6279\u6b21\u6570\u636e\u96c6\u5e94\u7528\u54ea\u4e2aauto_collate\u548ccollate_fn\u7684\u95ee\u9898"]
code: def __init__(
      self, collate_fns: Union[List[Callable], Callable]
  ) -> None:
      if isinstance(collate_fns, Sequence):
          self.collate_fns = lambda idx, lst: collate_fns[idx](lst)
      elif callable(collate_fns):
          self.collate_fns = lambda idx, lst: collate_fns(lst)
      else:
          self.collate_fns = lambda idx, lst: lst
  
file_path: fastNLP/fastNLP/core/dataloaders/torch_dataloader/mix_dataloader.py
imports: from typing import Optional, Callable, List, Union, Tuple, Dict, Sequence, Mapping
  import numpy
  from pkg_resources import parse_version
  from fastNLP.core.dataset import DataSet, Instance
  from fastNLP.core.samplers import PollingSampler, MixSequentialSampler, DopedSampler
  from fastNLP.envs.imports import _NEED_IMPORT_TORCH
  from fastNLP.core.collators import Collator
label_desc: Use image node_id 1 to create a new _MixCollateFn object  with example: obj = _MixCollateFn(collate_fns)